This command is available with the Predictive Analytics Module. Click here for more information about how to activate the module.
A team of researchers wants to use data about a borrower and the location of a property to predict the amount of a mortgage. Variables include the income, race, and gender of the borrower as well as the census tract location of the property, and other information about the borrower and the type of property. These data were adapted based on a public data set containing information on federal home loan bank mortgages. Original data from fhfa.gov.
The researcher can use the gradient boosted regression tree model to predict response values for new observations.
This example uses the dataset from Fit Model, but prediction is also available when you use Discover Key Predictors to create the model.
|Annual Income||Annual Income|
|Income Ratio||Income Ratio|
|Front End Ratio||Front End Ratio|
|Back End Ratio||Back End Ratio|
|Number of Borrowers||Number of Borrowers|
|Co-Borrower Age||Co-Borrower Age|
|Tract Minority Percent||Tract Minority Percent|
|Tract Income||Tract Income|
|Local Income||Local Income|
|Area Income||Area Income|
|First Time Home Buyer||First Time Home Buyer|
|Occupancy Code||Occupancy Code|
|Co-Borrower Race 4||Co-Borrower Race 4|
|Co-Borrower Race 5||Co-Borrower Race 5|
|Loan Purpose||Loan Purpose|
|Number of Units||Number of Units|
|Co-Borrower Race 3||Co-Borrower Race 3|
|Co-Borrower Gender||Co-Borrower Gender|
|Race 2||Race 2|
|Co-Borrower Ethnicity||Co-Borrower Ethnicity|
|Credit Score||Credit Score|
|Co-Borrower Credit Score||Co-Borrower Credit Score|
|Co-Borrower Race 2||Co-Borrower Race 2|
|Co-Borrower Race||Co-Borrower Race|
|Property Type||Property Type|
|Federal District||Federal District|
|State Code||State Code|
|County Code||County Code|
|Core Based Statistical Area||Core Based Statistical Area|